Much of the research activity of pharmaceutical companies in years past focused on the incremental improvement of existing drugs. These efforts involved repetitive rounds of compound modification and biological testing and have resulted in a large percentage of the available drugs directed to similar targets.
Approximately a dozen years ago, the emphasis of pharmaceutical research activities began shifting toward the purposeful discovery of novel chemical classes and novel molecular targets. This change in emphasis, and timely technological breakthroughs (e.g., molecular biology, laboratory automation, combinatorial chemistry) gave birth to high throughput screening, or HTS, which is now widespread throughout the biopharmaceutical industry.
High throughput screening involves several steps: creating an assay that is predictive of a particular physiological response; automating the assay so that it can be reproducibly performed a large number of times; and, sequentially testing samples from a chemical library to identify chemical structures able to “hit” the assay, suggesting that such structures might be capable of provoking the intended physiological response. Hits from the high throughput screen are followed up in a variety of secondary assays to eliminate artifactual results, particularly toxic compounds.
A high throughput screen could involve the testing of 200,000 compound samples or more, therefore requiring the use of lab robots. Examples of samples tested in such an assay include pure compounds saved in compound archives (e.g., certain pharmaceutical companies have chemical libraries that have been generated through decades of medicinal chemistry effort), samples purchased from academic sources, natural product extracts and libraries purposefully created for high throughput screening such as combinatorial libraries.
The assays used in high throughput screens are intended to detect the presence of chemical samples possessing specific biological or biochemical properties. These properties are chosen to identify compounds with the potential to elicit a specific biological response when applied in vivo. High throughput screens typically identify drug candidates rather than the agents that will ultimately be used as drugs. A compound of a certain chemical class found to have some level of desired biological property in a high throughput assay can then be the basis for synthesis of derivative compounds by medicinal chemists.
The assays fall into two broad categories: biochemical assays and cell-based assays. Biochemical assays utilize pure or semi-pure components outside of a cellular environment. Enzyme assays and receptor binding assays are typical examples of biochemical assays. Cell-based assays utilize intact cells in culture. Examples of such assays include luciferase reporter gene assays and calcium flux assays.
Biochemical assays are usually easier to perform and are generally less prone to artifacts than conventional cell-based assays. Compounds identified as “active” in a biochemical assay typically function according to a desired mechanism, decreasing the amount of follow-up experimentation required to confirm a compound's status as a “hit.” A major disadvantage of biochemical assays, however, is the lack of biological context. Compound “hits” from biochemical screens do not have to traverse a plasma membrane or other structures to reach and affect the target protein. Consequently, biochemical assays tend to be far less predictive of a compound's activity in an animal than cell-based assays.
Cell-based assays preserve much of the biological context of a molecular target. Compounds that cannot pass through the plasma membrane or that are toxic to the cell are not pursued. This context, however, adds complexity to the assay. Therefore conventional cell-based assays are much more prone to artifact or false positive results than are biochemical assays. Compounds that trigger complex toxic reactions or trigger apoptosis are particularly troublesome. Much of the labor devoted to conventional cell-based high throughput screening is directed to follow-up assays that detect false hits or hits that work by undesirable mechanisms.
If false positive or artifactual hits could be rapidly identified and eliminated, the ease and efficiency of biochemical assays could be approached in cell-based assays, while preserving the biological context. The result would be an assay with optimum throughput and optimum predictability of biological function. In short, a more efficient process for the discovery of new pharmaceuticals would be produced.